Ernst Glenda, Bosio Martín, Salvado Alejandro, Nogueira Facundo, Nigro Carlos, Borsini Eduardo
Respiratory Medicine Unit, British Hospital, Perdriel 74, C1280AEB Buenos Aires, Argentina.
Respiratory Medicine Unit, Hospital Clinics, Cordoba Avenue 2351, C1120AAF Buenos Aires, Argentina.
Sleep Disord. 2015;2015:314534. doi: 10.1155/2015/314534. Epub 2015 Aug 12.
Objective. According to current guidelines, autoscoring of respiratory events in respiratory polygraphy requires manual scoring. The aim of this study was to evaluate the agreement between automatic analysis and manual scoring to identify patients with suspected OSA. Methods. This retrospective study analyzed 791 records from respiratory polygraphy (RP) performed at home. The association grade between automatic scoring and manual scoring was evaluated using Kappa coefficient and the agreement using Bland and Altman test and intraclass correlation coefficient (CCI). To determine the accuracy in the identification of AHI ≥ 30 eV/h, the ROC curve analysis was used. Results. The population analyzed consisted of 493 male (62.3%) and 298 female patients, with an average age of 54.7 ± 14.20 years and BMI of 32.7 ± 8.21 kg/m(2). There was no significant difference between automatic and manual apnea/hypopnea indexes (aAHI, mAHI): aAHI 17.25 (SD: 17.42) versus mAHI 21.20 ± 7.96 (p; NS). The agreement between mAHI and aAHI to AHI ≥ 30 was 94%, with a Kappa coefficient of 0.83 (p < 0.001) and a CCI of 0.83. The AUC-ROC, sensitivity, and specificity were 0.99 (CI 95%: 0.98-0.99, p < 0.001), 86% (CI 95%: 78.7-91.4), and 97% (CI 95%: 96-98.3), respectively. Conclusions. We observed good agreement between automatic scoring and sequential manual scoring to identify subjects with AHI ≥ 30 eV/h.
目的。根据当前指南,呼吸多导睡眠图中呼吸事件的自动评分需要人工评分。本研究的目的是评估自动分析与人工评分之间的一致性,以识别疑似阻塞性睡眠呼吸暂停(OSA)的患者。方法。这项回顾性研究分析了791份在家中进行的呼吸多导睡眠图(RP)记录。使用Kappa系数评估自动评分与人工评分之间的关联等级,并使用Bland和Altman检验以及组内相关系数(CCI)评估一致性。为了确定识别呼吸暂停低通气指数(AHI)≥30次/小时的准确性,采用了ROC曲线分析。结果。分析的人群包括493名男性(62.3%)和298名女性患者,平均年龄为54.7±14.20岁,体重指数为32.7±8.21kg/m²。自动和人工呼吸暂停/低通气指数(aAHI,mAHI)之间无显著差异:aAHI为17.25(标准差:17.42),而mAHI为21.20±7.96(p;无统计学意义)。mAHI与aAHI对于AHI≥30的一致性为94%,Kappa系数为0.83(p<0.001),CCI为0.83。曲线下面积(AUC-ROC)、敏感性和特异性分别为0.99(95%置信区间:0.98-0.99,p<0.001)、86%(95%置信区间:78.7-91.4)和97%(95%置信区间:96-98.3)。结论。我们观察到自动评分与连续人工评分之间在识别AHI≥30次/小时的受试者方面具有良好的一致性。